AI-Powered 6G Dynamic Spectrum and Resource Allocation Optimization

Abstract

The invention relates to an AI-powered 6G dynamic spectrum and resource allocation optimization system developed for use in the telecommunications sector, particularly within the context of emerging 6G wireless communication technologies. It enables the optimization and allocation of frequency spectrum and network resources through geographic information (GIS) and semantic ontologies, meeting requirements for ultra-low latency, high data rate, and quality of service, and addressing the dynamic and complex resource management needs of 6G networks.

Description

1 TARIFF AI-Powered 6G Dynamic Spectrum and Resource Allocation Optimization Technical Area 5 The invention has implications for the telecommunications sector, particularly in the emerging field of 6G wireless communication. Developed for use within the scope of technologies, frequency spectrum and network geographic information (GIS – Geographic Information Systems) and semantic ontologies of resources ultra-low latency, high data allocation that enables optimization through this process. dynamic and complex resource management systems of 6G networks that meet speed and service quality requirements. AI-powered 6G dynamic spectrum and resource allocation that meets management needs. It is related to the optimization system. State of the Art Today, spectrum allocation is generally done using static or quasi-dynamic models, 15 Real spatial variables such as geographical location and land features are not adequately taken into account. It does not participate. Signal propagation suffers significant losses due to atmospheric and environmental factors. It exists. Different user and application requirements, such as Quality of Service (SLA), are real. There are shortcomings in timely and prioritized management. Frequency usage is high. Signal distribution and traffic variations in the regions are optimally integrated into existing systems. Because it is not properly managed, spectrum resources are used inefficiently. This situation is particularly problematic for autonomous vehicles. Communication in 6G scenarios requiring ultra-low latency, such as Industry 4.0 applications. This causes delays and decreased performance. As described above. due to the negative aspects and the inadequacy of the existing solutions regarding the issue. It has become necessary to make improvements in the technical field. 25 Purpose of the Invention The invention was created by drawing inspiration from existing situations and overcoming the aforementioned drawbacks. It aims to solve the problem. The main purpose of the invention is to network GIS and geographic and environmental data with semantic web ontologies. GIS, which semantically integrates assets, user services, and resources, is real. Time-based, location-based spectrum usage, coverage, and interference analysis maps. Prepared by geographically modeling regional frequency usage and signal attenuation, The semantic web, which constitutes the spatio-temporal distribution information of spectrum blocks. Network entities, user types, and services are defined using ontologies with technologies (RDF, OWL). categories and service levels are made sense by using logical inference and rules; 2 spatial systems that integrate geographic and semantic data and generate dynamic and intelligent allocation decisions. Decision-making algorithms supported by analysis, spectrum sensing, and semantic classification. using semantic ontology, spectrum measurements, service quality requirements and user defining priorities, according to both geographic and service priorities of spectrum blocks. 5 that enables dynamic and automatic determination where ultra-low latency is required. prioritizing applications, increasing spectrum efficiency, reducing interference, and saving energy. AI-powered 6G that saves energy and improves user experience. The goal is to provide a dynamic spectrum and resource allocation optimization system. Another purpose of the invention is to integrate CBS-based data, spectrum licenses, SLA requirements, and A rule engine that interprets user priorities using semantic ontologies, license and priority 10 By analyzing relationships, it classifies data and provides critical information for intelligent spectrum management. by combining information from semantic and GIS analyses, geographically enabling the inference. Spectrum blocks are actually determined according to priorities such as settlement, traffic density, and service quality. semantic adaptation and semantic-supported rules that perform time-based dynamic allocation. It provides optimization, monitors post-allocation SLA metrics, detects violations, and 15 Updating prioritization-based spectrum allocation policies, improving system performance. centrally located at the server layer, guaranteeing and optimizing service quality. coordinated to meet the demands for high speed and low latency in 6G technology. creating a flexible, scalable and intelligent spectrum management infrastructure, utilizing existing frequencies Overcoming complexity and hardware challenges with advanced GIS and semantic data integration, 20 Optimizing bandwidth usage and network through semantically supported decision-making mechanisms. AI-powered 6G dynamic spectrum and resource allocation that maximizes performance. The goal is to provide an optimization system. Figures to Help Understand the Invention 25 Figure 1 shows the general architecture of the system that is the subject of the invention. Explanation of Part References 1. Database (Input Module) 2. Server Module 30 3. CBS-Based Semantic Data Processing and Rule Engine 4. Dynamic Allocation and Decision-Making System 5. Performance Monitoring and Management Module 35 3 Detailed Description of the Invention This detailed description of the preferred configurations of the invention provides a better understanding of the subject matter. This is to facilitate understanding and will not create any limiting effects. The invention is artificial intelligence. It is a supported 6G dynamic spectrum and resource allocation optimization system, and user traffic, Real-time frequency usage from geographic frequency densities and spectrum measurements 5 database (1) which enables the collection and integration of data, central data collection It enables the storage, management, and flow of data between modules. Server module (2), data interpretation and classification through ontologies and Semantic data based on GIS that enables the creation of GIS-based allocation decisions. Processing and rule engine (3), by processing CBS and semantic data, intelligent spectrum blocks and 10 Dynamic allocation and decision-making system (4) which enables dynamic allocation, allocation Post-SLA compliance monitoring, prioritization and allocation in case of violations. Performance monitoring and management module that enables optimization (5) It includes. In the system that is the subject of the invention, the database (1) user traffic, geographical frequency densities and 15 Real-time data collection from spectrum measurements and spatial (GIS) analysis of this data. It provides functions for integrating with frequency information. The server module (2) collected centralized storage and management of all data, and fast transfer between modules. It ensures reliable data flow. Server module (2) high-capacity distributed database It includes technologies and real-time analytics infrastructure, thus enabling fast computation and 20 It provides infrastructure for decision-making mechanisms. GIS-based semantic data processing and rule-making. engine (3) CBS based data, spectrum licenses, SLA requirements and user It interprets its priorities through semantic ontologies; rule engine license and priority. It classifies data by analyzing their relationships. This layer provides intelligent spectrum management. It provides critical information extraction for the dynamic allocation and decision-making system (4) semantics and 25 By combining information from CBS analyses, geographic location, traffic density, and service It performs real-time dynamic allocation of spectrum blocks according to quality priorities. Semantic adaptation and optimization are achieved through semantically supported rules. Performance monitoring and management module (5) monitors post-allocation SLA metrics, violations It identifies and updates spectrum allocation policies based on prioritization. 30 It guarantees system performance and optimizes service quality. All of this... Modules are centrally coordinated at the server module (2) layer, in 6G technology. A flexible, scalable, and intelligent spectrum that meets the demands of high speed and low latency. It creates a management infrastructure. Thus, the existing frequency complexity and hardware These challenges are overcome through advanced GIS and semantic data integration. 35 Semantic-supported 4 Decision-making mechanisms optimize bandwidth usage and network performance. It maximizes.

Claims

REQUESTS 1. AI-powered 6G dynamic spectrum and resource allocation optimization system. Its characteristic is; real data from user traffic, geographic frequency densities and spectrum measurements 5 that enables the collection and integration of time-based frequency usage data. database (1), centralized storage and management of collected data, and data transfer between modules. Server module (2) that enables the flow of the server, Data interpretation and classification through ontologies and semantics CBS-based semantic data that enables the creation of CBS-based allocation decisions 10 processing and rule engine (3), Intelligent and dynamic allocation of spectrum blocks by processing CBS and semantic data. Dynamic allocation and decision-making system that enables (4), Post-allocation SLA compliance monitoring, prioritization in case of violations, and Performance monitoring and management module 15 that enables allocation optimization. (5) It includes.

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